Machines, such as off-highway trucks, tractors, dozers, loaders, earth moving equipment, or other construction machines, may have any number of structural components that are subject to fatigue damage which could lead to structural failures. One method for monitoring fatigue damage on a machine structure is to perform manual and/or visual inspections. However, such a method may be impractical for several reasons. For instance, adequate assessment may not be possible for structural components that are concealed or difficult to physically or visually access. Comprehensive assessment would also require substantial downtime and adversely impact productivity. Furthermore, manual inspections cannot easily account for cumulative wear or damage, or provide prognostic information which can be helpful in scheduling maintenance, repairs, and the like.
Some conventional techniques incorporate visual models of structural components which can be used to provide theoretical insight of damage or weak points of a machine frame. However, such techniques are based solely on theoretical events and do not account for the actual wear experienced in the field. Other conventional techniques employ gauges that can be placed on structures to electronically monitor various loads, strains and/or stress on the structure. Although such systems can be used to assess actual impacts on a machine frame, the data collected is discrete and localized, and thereby it fails to provide a comprehensive assessment of the entire frame. Furthermore, any comprehensive analysis of a frame based on such localized data fails to be updated frequently enough to enable real-time monitoring.
In one example, U.S. Pub. No. 2005/0017602 (the '602 publication) discloses a system configured to monitor structural fatigue based on peak strain or strain accumulation. Specifically, the '602 publication discloses wireless nodes having strain sensing devices that are configured to monitor strain and process strain data at the site of measurement. Although the '602 publication discloses a system that may be configured to monitor various aspects of fatigue, the data collected in the '602 publication is limited to discrete points of a given structural component, and thereby fails to be comprehensive of the entire component. The '602 publication similarly does not provide a comprehensive assessment of the entire component that can be updated frequently or on demand, such as in real-time, and in a cumulative manner.
In view of the foregoing disadvantages associated with conventional systems, a need exists for a solution which not only tracks the individual strains or damage actually experienced in the field, but also tracks the effect of those strains or damage on the entire machine frame. Moreover, there is a need for systems and methods that are capable of incorporating both field data as well as model data to provide a visual assessment of the entire machine frame. There is also a need for monitoring techniques that can provide both comprehensive as well as cumulative assessments of the machine frame that can be progressively and frequently updated. Furthermore, there is also a need to monitor information sufficient to provide reliable diagnostic and prognostic assessments of the machine frame.